Speech recognition refers to the process of converting an acoustic signal of spoken words into text. Historically speech recognition has been viewed as a complex problem due to a variety of factors that can affect the accuracy of the resulting text. Such factors include distortions in the acoustic signal caused by background noise as well as variations in the pronunciation, volume, and speed of the speaker. Accordingly the performance of automatic speech recognition systems may, in some cases, depend on the computing power available to process the acoustic signal and the techniques employed to recognize the speech.
Historically mobile computing devices have been limited in their ability to perform speech recognition. Some mobile computing devices, for example, may have lacked sufficient computing power to quickly process an acoustic signal and accurately convert the acoustic signal into text. In addition, limited network connectivity or limited network bandwidth may have prevented some computing devices from providing an acoustic signal to another computing device having sufficient processing power to process and convert the acoustic signal.
While attempts have been made to address these limitations, there remains room for improvement. One example approach, a mobile device may only be used to provide speech-derived text to a computing device if the computing device has installed a companion application that pairs the computing device with the mobile device. It will thus be appreciated that this example approach would not be suitable for computing devices that do not have the companion application installed.